Abstract
We study the stochastic resonance (SR) phenomenon in feed-forward networks of leaky integrate and fire (LIF) neurons. It is shown for various input frequencies, amplitudes and network sizes that the appropriate coupling strength can improve the output signal to noise ratio (SNR). We demonstrate that the value of the optimal coupling strength in the content of SR depends primarily on the absolute refractory period. Other circumstances, signal frequency, amplitude and network size play minor role to determine this value (see Figure 1), consequently it is possible to optimally pretune the system. The optimal coupling strength jumps to discrete values as the noise increases and we discuss the background of this phenomenon.
Highlights
Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Don H Johnson Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1471-2202-10-S1-info.pdf
We study the stochastic resonance (SR) phenomenon in feed-forward networks of leaky integrate and fire (LIF) neurons
It is shown for various input frequencies, amplitudes and network sizes that the appropriate coupling strength can improve the output signal to noise ratio (SNR)
Summary
Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Don H Johnson Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1471-2202-10-S1-info.pdf . Address: 1Department of Biophysics, KFKI Research Institute for Particle and Nuclear Physics of the Hungarian Academy of Sciences, Budapest, Hungary and 2Center for Complex Systems Studies, Kalamazoo College, Kalamazoo, MI, USA
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